Current data encryption technologies rely on the solution of complex numerical problems that present a formidable challenge to solve by brute force. Yet, when armed with a “key” to the solution, a legitimate user can easily gain access to the original, unencrypted data. This is the principle behind technologies such as AES (Advanced Encryption Standard), according to which data can be safely transmitted in encrypted form. However, the security provided by AES and other encryption technologies lasts only as long as a malicious party that intercepts the encrypted data does not have enough computing power and enough target data available to actually solve the problem in a brute force way (i.e., without the required key, but by trying all key possibilities until eventually the correct one is reached).
To hedge against the inevitable increases in computing power at the disposal of malicious parties worldwide (and which is poised to increase further still with the advent of quantum computers), those with a need for secure communications typically seek to increase the complexity of the numerical problems being presented for solution. However, one side effect of this escalation in problem complexity is that a legitimate user, i.e., one with the required key, must also now expend increasingly significant resources to protect and decrypt the data. Thus, while the resources needed by a legitimate user are still designed to be less than the resources needed to solve the problem by brute force, they present a non-negligible “tax” on various performance parameters such as throughput and energy consumption.
As such, a highly secure yet computationally economical data protection solution would be welcomed by the industry.